Optimization in Computational Chemistry and Molecular Biology

1. Front Matter

   Pages i-vii

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2. Predicting Protein Tertiary Structure using a Global Optimization Algorithm with Smoothing

   • Aqil Azmi, Richard H. Byrd, Elizabeth Eskow, Robert B. Schnabel, Silvia Crivelli, Thomas M. Philip et al.

   Pages 1-18

3. Methodology for Elucidating the Folding Dynamics of Peptides : Met-enkephalin Case Study

   • J. L. Klepeis, C. A. Floudas

   Pages 19-46

4. Energy Landscape Projections of Molecular Potential Functions

   • Andrew T. Phillips, J. Ben Rosen, Ken A. Dill

   Pages 47-55

5. Global Optimization and Sampling in the Context of Tertiary Structure Prediction: A Comparison of Two Algorithms

   • Volker A. Eyrich, Daron M. Standley, Richard A. Friesner

   Pages 57-71

6. Protein Folding Simulations by Monte Carlo Simulated Annealing and Multicanonical Algorithm

   • Yuko Okamoto

   Pages 73-90

7. Thermodynamics of Protein Folding — The Generalized-Ensemble Approach

   • Ulrich H. E. Hansmann

   Pages 91-105

8. An approach to detect the dominant folds of proteinlike heteropolymers from the statistics of a homopolymeric chain

   • Erik D. Nelson, Peter G. Wolynes, Jose’ N. Onuchic

   Pages 107-129

9. Gene Sequences are Locally Optimized for Global mRNA Folding

   • William Seffens, David Digby

   Pages 131-140

10. Structure Calculations of Symmetric Dimers using Molecular Dynamics/Simulated Annealing and NMR Restraints: The Case of the RIIα Subunit of Protein Kinase A

    • Dimitrios Morikis, Marceen Glavic Newlon, Patricia A. Jennings

    Pages 141-156

11. Structure Prediction of Binding Sites of MHC Class II Molecules based on the Crystal of HLA-DRB1 and Global Optimization

    • M. G. Ierapetritou, I. P. Androulakis, D. S. Monos, C. A. Floudas

    Pages 157-189

12. A Coupled Scanning and Optimization Scheme for Analyzing Molecular Interactions

    • Julie C. Mitchell, Andrew T. Phillips, J. Ben Rosen, Lynn F. Ten Eyck

    Pages 191-207

13. Improved Evolutionary Hybrids for Flexible Ligand Docking in AutoDock

    • William E. Hart, Chris Rosin, Richard K. Belew, Garrett M. Morris

    Pages 209-229

14. Electrostatic Optimization in Ligand Complementarity and Design

    • Erik Kangas, Bruce Tidor

    Pages 231-242

15. Exploring potential solvation sites of proteins by multistart local minimization

    • Sheldon Dennis, Carlos J. Camacho, Sandor Vajda

    Pages 243-261

16. On relative position of two biopolymer molecules minimizing the weighted sum of interatomic distances squared

    • Andrei B. Bogatyrev

    Pages 263-266

17. Visualization of Chemical Databases Using the Singular Value Decomposition and Truncated-Newton Minimization

    • Dexuan Xie, Tamar Schlick

    Pages 267-286

18. Optimization of Carbon and Silicon Cluster Geometry for Tersoff Potential using Differential Evolution

    • M. M. Ali, A. Törn

    Pages 287-300

19. D.C. Programming Approach for Large-Scale Molecular Optimization via the General Distance Geometry Problem

    • Thi Hoai An Le, Dinh Tao Pham

    Pages 301-339

20. Back Matter

    Pages 341-342

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Optimization in Computational Chemistry and Molecular Biology: Local and Global Approaches covers recent developments in optimization techniques for addressing several computational chemistry and biology problems. A tantalizing problem that cuts across the fields of computational chemistry, biology, medicine, engineering and applied mathematics is how proteins fold. Global and local optimization provide a systematic framework of conformational searches for the prediction of three-dimensional protein structures that represent the global minimum free energy, as well as low-energy biomolecular conformations.
Each contribution in the book is essentially expository in nature, but of scholarly treatment. The topics covered include advances in local and global optimization approaches for molecular dynamics and modeling, distance geometry, protein folding, molecular structure refinement, protein and drug design, and molecular and peptide docking.
Audience: The book is addressed not only to researchers in mathematical programming, but to all scientists in various disciplines who use optimization methods in solving problems in computational chemistry and biology.

• algorithm
• algorithms
• database
• databases
• global optimization
• linear optimization
• local optimization
• modeling
• molecular dynamics
• optimization
• programming
• simulation
• statistics
• thermodynamics
• visualization

• Princeton University, USA

  C. A. Floudas

• University of Florida, USA

  P. M. Pardalos

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